The present invention relates to computed tomography (CT) imaging apparatus, and more particularly, to image reconstruction methods.
In one current computed tomography system, an x-ray source emits a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system, termed the “imaging plane.” The x-ray beam passes through the object being imaged, such as a medical patient, and impinges upon an array of radiation detectors. The intensity of the transmitted radiation is dependent upon the attenuation of the x-ray beam by the object and each detector produces a separate electrical signal that is a measurement of the beam attenuation. The attenuation measurements from all the detectors are acquired separately to produce a transmission profile.
The source and detector array in a conventional CT system are rotated on a gantry or about a C-arm within the imaging plane and around the object so that the angle at which the x-ray beam intersects the object constantly changes. A group of x-ray attenuation measurements from the detector array at a given angle is referred to as a “view” and a “scan” of the object and comprises a set of views made at different angular orientations (θ) during one rotation of the x-ray source and detector. In a 2D scan, data is processed to construct an image that corresponds to a two dimensional slice taken through the object. The prevailing method for reconstructing an image from 2D data is referred to in the art as the filtered backprojection technique. This process converts the attenuation measurements from a scan into integers called “CT numbers” or “Hounsfield units”, which are used to control the brightness of a corresponding pixel on a display.
Traditional 3D cone-beam CT systems often include curved detectors with multiple rows or flat-panel based area detectors so that the scanning path is a single circle or a single arc. In a 3D scan the x-ray beam diverges to form a cone beam that passes through the object and impinges on a two-dimensional array of detector elements. Each view is thus a 2D array of x-ray attenuation measurements and the complete scan produces a 3D array of attenuation measurements. These cone-beam CT systems have been widely used in diagnostic radiology where a multi-row detector is utilized, in interventional radiology where a flat-panel detector is mounted on a C-arm gantry to implement cone-beam CT, and in cone-beam CT image-guided radiation therapy where one or two flat-panel detectors are mounted on the slow gantry to perform cone-beam CT data acquisition.
However, the single circle/arc scanning path does not generate sufficient projections for a mathematically exact image reconstruction. In particular, due to the divergent paths followed by the x-ray beams, the data is incomplete or some data is “missed”. Referring now to FIG. 1, an x-ray source 1 is directed toward an object 2 such that x-ray beams 3 impinge upon the object 2 on the way toward a detector array 4.
Referring to FIGS. 1 through 3, during an imaging process, the x-ray source 1 is rotated about a source trajectory 5 that is mirrored by the detector array 4. However, due to the diverging paths followed by the x-ray beams 3, no information is obtained about rotational axis 6 defined by the source trajectory 5. As such, although the object 2 of the imaging process has an oval shape, the beam paths represented in FIG. 2 only gather data along two circular cross-sectional areas separated by “missing data” 7. This missing data 7 is a problem that has historically plagued cone-beam CT data acquisition.
In particular, when an image is reconstructed using data with substantial missing data 7, artifacts are induced in the reconstructed image that significantly degrade the diagnostic quality of the image. That is, even if the area of the object 2 corresponding to the missing data 7 is not of diagnostic interest, the missing data 7 affects the overall quality of the image by inducing artifacts that can stray throughout the image.
To compensate for this missing data 7, many approximate image reconstruction methods have been developed for very small cone-angles (e.g., up to 5 degrees) as exemplified in U.S. Pat. Nos. 5,270,926; 6,104,775; 5,257,183; 5,625,660, 6,097,784; 6,219,441, and 5,400,255. However, when large cone-angles are used, such as in 128-slice helical CT imaging processes and flat-panel detector based cone-beam CT imaging processes, these approximate image reconstruction methods are insufficient to compensate for cone-beam artifacts caused by the missing data 7.
Therefore, it would be desirable to have a system and method for reconstructing data acquired using a cone-beam CT imaging process that has reduced artifacts and that is not limited by cone-angle, extended data acquisition processes, or overly cumbersome reconstruction algorithms.